Instructions to use imagepipeline/SDXL-Unstable-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use imagepipeline/SDXL-Unstable-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("imagepipeline/SDXL-Unstable-Diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- fa0ba41066ac00adda358f1c16595637e3ed7f4ccac65c88ed33d7ae35e814a8
- Size of remote file:
- 246 MB
- SHA256:
- b05d3b14f9c879001d6fbebc18208758eccfcf2b8ef736c17c3e06ae8477a24f
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